Kecheng Tang, Jiawen Zhang, Yuji Shen, Chen Li, Gaoqi He
{"title":"KDPM:用于疏散场景模拟的知识驱动动态感知模型","authors":"Kecheng Tang, Jiawen Zhang, Yuji Shen, Chen Li, Gaoqi He","doi":"10.1002/cav.2279","DOIUrl":null,"url":null,"abstract":"<p>Evacuation scene simulation has become one important approach for public safety decision-making. Although existing research has considered various factors, including social forces, panic emotions, and so forth, there is a lack of consideration of how complex environmental factors affect human psychology and behavior. The main idea of this paper is to model complex evacuation environmental factors from the perspective of knowledge and explore pedestrians' emergency response mechanisms to this knowledge. Thus, a knowledge-driven dynamic perception model (KDPM) for evacuation scene simulation is proposed in this paper. This model combines three modules: knowledge dissemination, dynamic scene perception, and stress response. Both scenario knowledge and hazard source knowledge are extracted and expressed. The improved intelligent agent perception model is designed by adopting position determination. Moreover, a general adaptation syndrome (GAS) model is first presented by introducing a modified stress system model. Experimental results show that the proposed model is closer to the reality of real data sets.</p>","PeriodicalId":50645,"journal":{"name":"Computer Animation and Virtual Worlds","volume":"35 3","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"KDPM: Knowledge-driven dynamic perception model for evacuation scene simulation\",\"authors\":\"Kecheng Tang, Jiawen Zhang, Yuji Shen, Chen Li, Gaoqi He\",\"doi\":\"10.1002/cav.2279\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Evacuation scene simulation has become one important approach for public safety decision-making. Although existing research has considered various factors, including social forces, panic emotions, and so forth, there is a lack of consideration of how complex environmental factors affect human psychology and behavior. The main idea of this paper is to model complex evacuation environmental factors from the perspective of knowledge and explore pedestrians' emergency response mechanisms to this knowledge. Thus, a knowledge-driven dynamic perception model (KDPM) for evacuation scene simulation is proposed in this paper. This model combines three modules: knowledge dissemination, dynamic scene perception, and stress response. Both scenario knowledge and hazard source knowledge are extracted and expressed. The improved intelligent agent perception model is designed by adopting position determination. Moreover, a general adaptation syndrome (GAS) model is first presented by introducing a modified stress system model. Experimental results show that the proposed model is closer to the reality of real data sets.</p>\",\"PeriodicalId\":50645,\"journal\":{\"name\":\"Computer Animation and Virtual Worlds\",\"volume\":\"35 3\",\"pages\":\"\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2024-05-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Animation and Virtual Worlds\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/cav.2279\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Animation and Virtual Worlds","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cav.2279","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
KDPM: Knowledge-driven dynamic perception model for evacuation scene simulation
Evacuation scene simulation has become one important approach for public safety decision-making. Although existing research has considered various factors, including social forces, panic emotions, and so forth, there is a lack of consideration of how complex environmental factors affect human psychology and behavior. The main idea of this paper is to model complex evacuation environmental factors from the perspective of knowledge and explore pedestrians' emergency response mechanisms to this knowledge. Thus, a knowledge-driven dynamic perception model (KDPM) for evacuation scene simulation is proposed in this paper. This model combines three modules: knowledge dissemination, dynamic scene perception, and stress response. Both scenario knowledge and hazard source knowledge are extracted and expressed. The improved intelligent agent perception model is designed by adopting position determination. Moreover, a general adaptation syndrome (GAS) model is first presented by introducing a modified stress system model. Experimental results show that the proposed model is closer to the reality of real data sets.
期刊介绍:
With the advent of very powerful PCs and high-end graphics cards, there has been an incredible development in Virtual Worlds, real-time computer animation and simulation, games. But at the same time, new and cheaper Virtual Reality devices have appeared allowing an interaction with these real-time Virtual Worlds and even with real worlds through Augmented Reality. Three-dimensional characters, especially Virtual Humans are now of an exceptional quality, which allows to use them in the movie industry. But this is only a beginning, as with the development of Artificial Intelligence and Agent technology, these characters will become more and more autonomous and even intelligent. They will inhabit the Virtual Worlds in a Virtual Life together with animals and plants.